Governance for action-taking AI agents

Know what your AI agents did, what policy says, and what still needs review.

McPherson Governance evaluates supported OpenClaw activity against explicit policy and produces a readable record of what was attempted, what completed, what policy would have decided, and what remains unknown.

The current release operates in shadow mode. It has no authority to block, approve, deny, or rewrite your agents’ actions.

Public release v0.5.1 · Shadow-only
The accountability problem

An activity log is not the same as governance evidence.

A tool event can be useful without answering the questions an operator, reviewer, or incident owner actually needs resolved.

  • A log may not proveThe correct action occurred.
  • A log may not provePolicy was followed.
  • A log may not proveApproval was required or obtained.
  • A log may not proveThe external action completed.
  • A log may not proveThe evidence is sufficient.
  • A log may not proveThe issue is resolved.
The product in three parts

Observation, policy, and evidence that stay honest about their limits.

01

OpenClaw plugin

Observes supported tool attempts and completions through the configured OpenClaw path.

02

Policy service

Evaluates mapped activity against explicit governance rules and records the decision the policy would have produced.

03

Observa

Turns governance evidence into an operator-readable record of what happened, what needs review, and what should not be assumed.

How the governed path works

A readable path from proposal to review.

Each stage has a distinct job. The current public release observes and records; it does not give remote policy authority over execution.

  1. Agent proposesA tool action enters the supported OpenClaw path.
  2. Plugin observesThe configured attempt is described with minimized metadata.
  3. Policy evaluatesMapped activity is checked against explicit rules.
  4. Evidence is boundAttempt, decision, and observed completion are correlated.
  5. Observa explainsFacts, gaps, and policy results become readable.
  6. Operator reviewsA person decides what requires follow-up.
Verification and proof

Restrained claims. Identified release.

The evidence below applies to the verified v0.5.1 public release. It separates McPherson AI release verification, ClawHub availability, and the isolated public-install smoke test.

250 release checks passed0 failures · 0 skipped · McPherson AI verification
Public ClawHub package availableLatest v0.5.1 · clean scan status
Public-install smoke test passedExact ClawHub artifact · isolated named profile
Shadow-only authority boundary verifiedActive enforcement remains false
Managed starting point

Founding Governance Setup

For OpenClaw operators who want help mapping agent activity, defining initial policy, reviewing evidence quality, and identifying coverage gaps before considering enforcement.

Company lanes

Governance leads. Operating experience stays visible.

Governance

McPherson Governance

OpenClaw-first policy evaluation, evidence binding, review, approvals, incident recovery, and eventual bounded enforcement.

Explore Governance →

QSR Systems

Built from operations

Restaurant operating workflows developed from sixteen years of direct operating experience.

See QSR Systems →

Workflow Services

Narrow, accountable builds

Workflow mapping, source-of-truth discovery, approval design, regulated discovery, and narrow automation builds.

See Workflow Services →